Shresth Rana

Co-Founder

Los Angeles, California, United States2 yrs 9 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Led AI initiatives from seed to scale at Grapevine.
Developed real-time recommendation systems for over 500K users.
Shipped LLM infrastructure for scalable NLP applications.

Stackforce AI infers this person is a SaaS-focused AI/ML expert with strong capabilities in recommendation systems and NLP.

Contact

Skills

Core Skills

Ai/mlRecommendation SystemsNlpLlm InfrastructureComputer Vision

Other Skills

Real-time ProcessingData EngineeringModel ServingPrompt EngineeringExplainable AIImage Processing

About

now: cs at usc before: built and scaled search, recommendations, and llm infrastructure at grapevine (sequoia india-backed), watched ideas collide with reality. experienced what it means to scale intelligence, what early-stage building teaches you about cognition and human behaviour.

Experience

Grapevine

Applied AI Systems, Founding Team

Aug 2023 – Jul 2025 · 1 yr 11 mos · Bengaluru, Karnataka, India · On-site

> 10th hire at Grapevine, backed by Peak XV (fka Sequoia Capital India & SEA), led AI from seed to Series-A, scaling products from zero to over half a million users, including recommendation engines, AI interviews, and hyper-personalized news at lightning speed.
Led AI/ML initiatives from zero to scale:
Core Recommendation System: real-time(< 100ms), context-aware feed ranking (scaled to 500K+ users); built retriever + scorer pipelines with dynamic weights, evaluated with CTR, swipe depth.
Round1 AI Interviews: AI voice agents for screening interviews (scaled to 1M+ minutes and counting); built prompt orchestration, streaming inference, and entire stack ranking strategy on interview transcripts.
News AI: personalized news briefings with fast retrieval + summarization (scaled to 3M+ swipes); used fast retrieval (BM25 + embeddings), personalized re-ranking policy.
> Own full stack: data → model → infra → product
> Focus on scalable ML systems, eval tooling, and tight latency constraints
> Helped shape Grapevine’s internal AI infra and product strategy

AI/MLRecommendation SystemsReal-time ProcessingData EngineeringNLP

Ibm

2 roles

Data Scientist, Artificial Intelligence

Sep 2022 – Jul 2023 · 10 mos · Bengaluru, Karnataka, India · On-site

> shipped infra and tooling to build LLM accelerators for client-side deployment + automated prompt augmentation and model serving architectures to make NLP apps actually scale in real-time.
LLM infra stuff i worked on:
automated prompt augmentation for dynamic, context-aware inputs
scalable model serving for low latency applications

LLM InfrastructureNLPModel ServingPrompt Engineering

Semester Intern, Cognitive Data Science

Jan 2022 – Jun 2022 · 5 mos · Bengaluru, Karnataka, India · Remote

> built computer vision pipelines for edge devices. shipped image defect detection systems optimized for low-latency deployment + worked on explainable ai with grad-cam to make quality classification models less of a black box.

Computer VisionExplainable AIImage Processing